化工矿物与加工2026，Vol.55Issue(1)：50-57,8.DOI:10.16283/j.cnki.hgkwyjg.2026.01.007
岩石抗剪强度参数的正态模糊数线性回归估计
Determination of rock shear strength parameters based on linear regression method of normal fuzzy numbers
摘要
Abstract
The test values of rock shear strength usually have randomness,fuzziness and variability,which makes the shear strength parameters calculated by Mohr-Coulomb criterion uncertain.In this paper,through the direct shear test of limestone,it is found that with the increase of lateral stress,the average value of shear strength shows an upward trend,and the standard deviation of shear strength under the same lateral stress increases gradually,which shows that the discreteness of shear strength increases with the increase of lateral stress.The shear strength test data under the same lateral stress obey the normal distribution.This conclusion conforms to the Lyapunov theorem,so the normal fuzzy number is used to describe the shear strength interval under the same lateral stress.At the same time,it is concluded that the cohesion and internal friction coefficient obey the normal distribution through theoretical deriva-tion.Based on this conclusion and the principle of fuzzy least squares method,a normal fuzzy number linear regression estimation method is proposed to characterize the interval characteristics of rock shear strength parameters,and the goodness of fit evaluation index is selected to evaluate the performance of rock shear strength parameters characterized by this method.The results show that this method can accurately estimate the normal distribution interval of rock shear strength parameters and provide a new idea for the determination of rock shear strength parameters.关键词
岩石抗剪强度/平推直剪试验/正态模糊数/不确定性/正态分布/最小二乘法/侧向应力/拟合优度Key words
rock shear strength/flat push direct shear test/normal fuzzy number/uncertainty/normal distribution/ordinary least squares/lateral stress/goodness-of-fit分类
建筑与水利引用本文复制引用
李斌,高尚,何治良,张敏,顾鑫,苟淦昊..岩石抗剪强度参数的正态模糊数线性回归估计[J].化工矿物与加工,2026,55(1):50-57,8.基金项目
国家自然科学基金项目(51904248) （51904248）
四川省自然科学基金项目(2024NSFSC0975). （2024NSFSC0975）
